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In the last years, the public interest in epidemiology and mathematical modeling of disease spread has increased - mainly caused by the COVID-19 pandemic, which has emphasized the urgent need for accurate and timely modelling of disease transmission. However, even prior to that, mathematical modelling has been used for describing the dynamics and spread of infectious diseases, which is vital for developing effective interventions and controls, e.g., for vaccination campaigns and social restrictions like lockdowns. The forecasts and evaluations provided by these models influence political actions and shape the measures implemented to contain the virus.
This research contributes to the understanding and control of disease spread, specifically for Dengue fever and COVID-19, making use of mathematical models and various data analysis techniques. The mathematical foundations of epidemiological modelling, as well as several concepts for spatio-temporal diffusion like ordinary differential equation (ODE) models, are presented, as well as an originally human-vector model for Dengue fever, and the standard (SEIR)-model (with the potential inclusion of an equation for deceased persons), which are suited for the description of COVID-19. Additionally, multi-compartment models, fractional diffusion models, partial differential equations (PDE) models, and integro-differential models are used to describe spatial propagation of the diseases.
We will make use of different optimization techniques to adapt the models to medical data and estimate the relevant parameters or finding optimal control techniques for containing diseases using both Metropolis and Lagrangian methods. Reasonable estimates for the unknown parameters are found, especially in initial stages of pandemics, when little to no information is available and the majority of the population has not got in contact with the disease. The longer a disease is present, the more complex the modelling gets and more things (vaccination, different types, etc.) appear and reduce the estimation and prediction quality of the mathematical models.
While it is possible to create highly complex models with numerous equations and parameters, such an approach presents several challenges, including difficulties in comparing and evaluating data, increased risk of overfitting, and reduced generalizability. Therefore, we will also consider criteria for model selection based on fit and complexity as well as the sensitivity of the model with respect to specific parameters. This also gives valuable information on which political interventions should be more emphasized for possible variations of parameter values.
Furthermore, the presented models, particularly the optimization using the Metropolis algorithm for parameter estimation, are compared with other established methods. The quality of model calculation, as well as computational effort and applicability, play a role in this comparison. Additionally, the spatial integro-differential model is compared with an established agent-based model. Since the macroscopic results align very well, the computationally faster integro-differential model can now be used as a proxy for the slower and non-traditionally optimizable agent-based model, e.g., in order to find an apt control strategy.
Artificial neural networks is a popular field of research in artificial intelli-
gence. The increasing size and complexity of huge models entail certain
problems. The lack of transparency of the inner workings of a neural net-
work makes it difficult to choose efficient architectures for different tasks.
It proves to be challenging to solve these problems, and with a lack of in-
sightful representations of neural networks, this state of affairs becomes
entrenched. With these difficulties in mind a novel 3D visualization tech-
nique is introduced. Attributes for trained neural networks are estimated
by utilizing established methods from the area of neural network optimiza-
tion. Batch normalization is used with fine-tuning and feature extraction to
estimate the importance of different parts of the neural network. A combi-
nation of the importance values with various methods like edge bundling,
ray tracing, 3D impostor and a special transparency technique results in a
3D model representing a neural network. The validity of the extracted im-
portance estimations is demonstrated and the potential of the developed
visualization is explored.
Leichte Sprache (LS, easy-to-read German) is a simplified variety of German. It is used to provide barrier-free texts for a broad spectrum of people, including lowliterate individuals with learning difficulties, intellectual or developmental disabilities (IDD) and/or complex communication needs (CCN). In general, LS authors are proficient in standard German and do not belong to the aforementioned group of people. Our goal is to empower the latter to participate in written discourse themselves. This requires a special writing system whose linguistic support and ergonomic software design meet the target group’s specific needs. We present EasyTalk a system profoundly based on natural language processing (NLP) for assistive writing in an extended variant of LS (ELS). EasyTalk provides users with a personal vocabulary underpinned with customizable communication symbols and supports in writing at their individual level of proficiency through interactive user guidance. The system minimizes the grammatical knowledge needed to produce correct and coherent complex contents by intuitively formulating linguistic decisions. It provides easy dialogs for selecting options from a natural-language paraphrase generator, which provides context-sensitive suggestions for sentence components and correctly inflected word forms. In addition, EasyTalk reminds users to add text elements that enhance text comprehensibility in terms of audience design (e.g., time and place of an event) and improve text coherence (e.g., explicit connectors to express discourse-relations). To tailor the system to the needs of the target group, the development of EasyTalk followed the principles of human-centered design (HCD). Accordingly, we matured the system in iterative development cycles, combined with purposeful evaluations of specific aspects conducted with expert groups from the fields of CCN, LS, and IT, as well as L2 learners of the German language. In a final case study, members of the target audience tested the system in free writing sessions. The study confirmed that adults with IDD and/or CCN who have low reading, writing, and computer skills can write their own personal texts in ELS using EasyTalk. The positive feedback from all tests inspires future long-term studies with EasyTalk and further development of this prototypical system, such as the implementation of a so-called Schreibwerkstatt (writing workshop)
In a world where language defines the boundaries of one's understanding, the words of Austrian philosopher Ludwig Wittgenstein resonate profoundly. Wittgenstein's assertion that "Die Grenzen meine Sprache bedeuten die Grenzen meiner Welt" (Wittgenstein 2016: v. 5.6) underscores the vital role of language in shaping our perceptions. Today, in a globalized and interconnected society, fluency in foreign languages is indispensable for individual success. Education must break down these linguistic barriers, and one promising approach is the integration of foreign languages into content subjects.
Teaching content subjects in a foreign language, a practice known as Content Language Integrated Learning (CLIL), not only enhances language skills but also cultivates cognitive abilities and intercultural competence. This approach expands horizons and aligns with the core principles of European education (Leaton Gray, Scott & Mehisto 2018: 50). The Kultusministerkonferenz (KMK) recognizes the benefits of CLIL and encourages its implementation in German schools (cf. KMK 2013a).
With the rising popularity of CLIL, textbooks in foreign languages have become widely available, simplifying teaching. However, the appropriateness of the language used in these materials remains an unanswered question. If textbooks impose excessive linguistic demands, they may inadvertently limit students' development and contradict the goal of CLIL.
This thesis focuses on addressing this issue by systematically analyzing language requirements in CLIL teaching materials, emphasizing receptive and productive skills in various subjects based on the Common European Framework of Reference. The aim is to identify a sequence of subjects that facilitates students' language skill development throughout their school years. Such a sequence would enable teachers to harness the full potential of CLIL, fostering a bidirectional approach where content subjects facilitate language learning.
While research on CLIL is extensive, studies on language requirements for bilingual students are limited. This thesis seeks to bridge this gap by presenting findings for History, Geography, Biology, and Mathematics, allowing for a comprehensive understanding of language demands. This research endeavors to enrich the field of bilingual education and CLIL, ultimately benefiting the academic success of students in an interconnected world.
The trends of industry 4.0 and the further enhancements toward an ever changing factory lead to more mobility and flexibility on the factory floor. With that higher need of mobility and flexibility the requirements on wireless communication rise. A key requirement in that setting is the demand for wireless Ultra-Reliability and Low Latency Communication (URLLC). Example use cases therefore are cooperative Automated Guided Vehicles (AGVs) and mobile robotics in general. Working along that setting this thesis provides insights regarding the whole network stack. Thereby, the focus is always on industrial applications. Starting on the physical layer, extensive measurements from 2 GHz to 6 GHz on the factory floor are performed. The raw data is published and analyzed. Based on that data an improved Saleh-Valenzuela (SV) model is provided. As ad-hoc networks are highly depended onnode mobility, the mobility of AGVs is modeled. Additionally, Nodal Encounter Patterns (NEPs) are recorded and analyzed. A method to record NEP is illustrated. The performance by means of latency and reliability are key parameters from an application perspective. Thus, measurements of those two parameters in factory environments are performed using Wireless Local Area Network (WLAN) (IEEE 802.11n), private Long Term Evolution (pLTE) and 5G. This showed auto-correlated latency values. Hence, a method to construct confidence intervals based on auto-correlated data containing rare events is developed. Subsequently, four performance improvements for wireless networks on the factory floor are proposed. Of those optimization three cover ad-hoc networks, two deal with safety relevant communication, one orchestrates the usage of two orthogonal networks and lastly one optimizes the usage of information within cellular networks.
Finally, this thesis is concluded by an outlook toward open research questions. This includes open questions remaining in the context of industry 4.0 and further the ones around 6G. Along the research topics of 6G the two most relevant topics concern the ideas of a network of networks and overcoming best-effort IP.
Gemeinsame Prüfungsordnung für den Bachelorstudiengang „Gewässerkunde und Wasserwirtschaft“ an der Hochschule Koblenz und der Universität Koblenz (Kooperativer Bachelorstudiengang)
Gemeinsame Prüfungsordnung für den Masterstudiengang „Gewässerkunde und Wasserwirtschaft“ an der Universität Koblenz und der Hochschule Koblenz (Kooperativer Masterstudiengang)
Satzung zur Sicherung guter wissenschaftlicher Praxis an der Universität Koblenz
Erste Ordnung zur Änderung der Wahlordnung für die Wahlen der Organe der Universität Koblenz
Prüfungsordnung für die Prüfung im Bachelorstudiengang Computational Social Science an der Universität Koblenz
Einunddreißigste Ordnung zur Änderung der Prüfungsordnung für die Prüfung im lehramtsbezogenen Bachelorstudiengang an der Universität Koblenz
Siebenundzwanzigste Ordnung zur Änderung der Prüfungsordnung für die Prüfung in den Masterstudiengängen für das Lehramt an Grundschulen, das Lehramt an Realschulen plus, das Lehramt an Förderschulen sowie das Lehramt an Gymnasien an der Universität Koblenz
Achtzehnte Ordnung zur Änderung der Ordnung für die Prüfung im lehramtsbezogenen Bachelorstudiengang berufsbildende Schulen an der Universität Koblenz und der Hochschule Koblenz
Siebzehnte Ordnung zur Änderung der Ordnung für die Prüfung im Masterstudiengang für das Lehramt an berufsbildenden Schulen an der Universität Koblenz und der Hochschule Koblenz
Achtundzwanzigste Ordnung zur Änderung der Ordnung für die Prüfung im lehramtsbezogenen Zertifikatsstudiengang (Erweiterungsprüfung) an der Universität Koblenz und der Hochschule Koblenz
Dritte Ordnung zur Änderung der Gemeinsamen Prüfungsordnung für die Bachelor- und Masterstudiengänge des Fachbereichs Informatik an der Universität Koblenz
Vierundzwanzigste Ordnung zur Änderung der Prüfungsordnung für die Prüfung im Zwei-Fach-Bachelorstudiengang an der Universität Koblenz
Satzung zur Festsetzung von Zulassungszahlen an der Universität Koblenz für das Studienjahr 2023/2024
Satzung zur Festsetzung der Normwerte für den Ausbildungsaufwand (Curricularnormwerte) der Universität Koblenz
Satzung der Universität Koblenz über das Auswahlverfahren in zulassungsbeschränkten Studiengängen
Qualitätssicherungskonzept für das Promotions- und Habilitationswesen der Universität Koblenz (Satzung über die Genehmigung von Promotions- und Habilitationsordnungen)
Dritte Ordnung zur Änderung der Prüfungsordnung für Studierende des Bachelorstudiengangs „Pädagogik“ (B.A.) und des Masterstudiengangs „Erziehungswissenschaft mit dem Schwerpunkt Forschung und Entwicklung in Organisationen“ (M.A.) des Fachbereichs 1: Bildungswissenschaften an der Universität Koblenz
Ordnung zum Betrieb eines Forschungsinformationssystems an der Universität Koblenz (FIS-Ordnung)
Organic binder mixtures and process additives have been used in refractory materials for a long time due to their property-improving effect. Coal tar pitches in particular can contain thousands of chemical compounds, of which especially polycyclic aromatic hydrocarbons (PAHs) are known to be carcinogenic and mutagenic and thus pose a risk to both the environment and human health. However, despite intensive research, the exact structure of these carbon mixtures is still not fully clarified. This is becoming an increasing problem, especially with regard to more stringent legal requirements arising from REACH, the European Chemicals Regulation for the Registration, Evaluation, Authorization and Restriction of Chemicals. Furthermore, the knowledge of the structural and chemical composition is also of great importance for optimal processing of the carbon mixtures to high-quality technical products. In the present work, an analytical strategy for the investigation of complex carbon mixtures containing PAHs is developed. Due to their complexity, a combination of different methods is used, including elemental analysis, solvent extraction, thermogravimetry, differential thermal analysis, raman and infrared spectroscopy as well as high-resolution mass spectrometry. In addition, a procedure for the evaluation of mass spectrometric data based on multivariate statistical methods such as hierarchical cluster analysis and principal component analysis is developed. The application of the developed analytical strategy to various industrially used carbon-based binder mixtures allowed the elucidation of characteristic properties, including aromaticity, molecular mass distribution, degree of alkylation and elemental composition. It was also shown that combining high-resolution time-of-flight mass spectrometry with multivariate statistical data analysis is a fast and effective tool for the classification of complex binder mixtures and the identification of characteristic molecular structures. In addition, the analytical strategy was applied to manufactured refractory products. Despite the small amount of the contained organic phase, characteristic structural features of each sample could be identified and extracted, which enabled an unambiguous classification of the refractory products.
Die Geometrie unseres Anschauungsraumes – die euklidische Geometrie – ist für einen allgemeinbildenden Mathematikunterricht elementar. Seitens der Mathematiklehrkraft stellt grundsätzlich ihr Fachwissen das Fundament des Unterrichtens dar. Als Teil ihres Professionswissens sollten Mathematiklehrkräfte prinzipiell über ein Fachwissen verfügen, das in Bezug zur akademischen Mathematik den unterrichtlichen Anforderungen der schulischen Mathematik gerecht wird.
Die im Rahmen der Dissertation entwickelte Theorie des metrisch-normalen euklidischen Raumes charakterisiert sich in ihrer perspektivischen Dualität, der mathematischen Stringenz eines axiomatisch-deduktiven Vorgehens auf der einen und der Berücksichtigung der fachdidaktischen Anforderungen an Mathematiklehrkräfte auf der anderen Seite; sie hebt sich darin von bestehenden Theorien ab.